Our duo of hurricanes, Harvey and Irma, have elevated the perceived risks of climate change in a lot of people’s minds. Are these disasters, and the record heat in many places, a sign of climate warming already out of control?
The quick answer is maybe, but climate scientists will need a lot more data and probably a few more years to know whether we are seeing a blip or a trend. From a persuasion perspective, the fascinating thing to me is that the climate science “sides” have reversed because of the storms. And here I am only talking about non-scientists on social media.
Last winter I saw climate skeptics (or deniers in some cases) proclaiming climate change a hoax because it was cold outside. The scientists and pro-climate-change folks mocked those poor souls for not understanding the difference between anecdotal evidence and science. You can’t determine a long term trend by looking out the window, say all scientists. And if you think you can, you’re being a big dope who doesn’t know the first thing about science.
If you don’t understand that anecdotal data in isolation is generally useless to scientists, you don’t understand anything about science. A year ago, that described a lot of climate skeptics who were looking out their windows, seeing snow, and declaring climate change a hoax.
But that was last year. This week the sides reversed. Now I keep seeing climate alarmists on social media looking at the hurricanes and declaring them strong evidence of climate change. They might be right. But if they are, it is by coincidence and not by science. Scientists say it is too early to tell. So now we have a bizarre situation in which the pro-science side is disagreeing with the scientists on their own side. That’s what confirmation bias gets you. Both sides see anecdotal evidence as real. Both sides think they respect and understand the basics of science. Both sides are wrong.
Please excuse my generalities here. Obviously there are plenty of smart people on both sides who understand that anecdotal information is not confirmation of anything. But in terms of what I see on social media, the hurricanes have turned a lot of people on the pro-science side into believers in anecdotal evidence. Here’s one example. Read from bottom up.
And this brings me to my topic of the day: How do you know when to trust experts? My hypothesis is that people who have the most experience in the real world trust experts the least. To make that point, allow me to give you a brief tour of my experience with experts.
When I was a kid, scientists seemed to agree on what constituted good nutrition. They even put that knowledge into a handy visual aid involving a food pyramid, and provided it to every school. We now understand the science behind it to be bunk.
I’m old enough to have observed fitness experts revising their advice countless times. I’m no longer sure if stretching is good or bad. And the exercise experts also had the nutrition stuff wrong, along with the rest of the world, for most of my lifetime.
When I was a kid, Sigmund Freud was considered the leading expert on psychology even though he was dead. Now the experts in psychology considers Freud a fraud. His science wasn’t science at all.
When I was young, I assumed experts could pick stocks better than a monkey with a dart board. It turns out I was wrong. Index funds with no experts whatsoever routinely outperform the expert stock-pickers.
I have a degree in economics and an MBA from UC Berkeley. I did financial projections for a living, first at a major bank and later at the local phone company. People considered me an expert in that narrow field. In a number of cases, I got to track how my projections compared to actual results. They were rarely close. As an expert, I deserved no credibility whatsoever. And for a good reason. My projections required human judgment on lots of variables, so the output was little more than guessing and massaging the numbers to meet my boss’s expectations.
Some of you know I lost my ability to speak for over three years because of a bizarre disorder called spasmodic dysphonia. The experts almost unanimously agreed that the source of the spasmodic dysphonia is in the brain, not the vocal cords. I ended up diagnosing myself correctly after my primary care doctor and his recommended specialists were totally stumped. (I figured it out using Google.) Once I knew the problem, I found the one surgeon in the world who claimed he could fix my problem by rewiring the nerve pathways in my neck. The operation was a success, and I recovered from an “incurable” problem. Had I listened to 99% of the experts who said the problem was in my brain, I would not have considered an operation on my neck.
I could go on like this for hours, but I think you start to see my point. At my age, and given my type of experience, I have seen experts get the big stuff wrong lots of times, even when that seemed deeply unlikely.
That brings us to climate change. The experts are strongly aligned on one side. If you have neither the age nor the experience to know how often experts can be wrong, you probably assume the experts are credible. But if you have my type of experience, watching the fields of finance, diet, exercise, psychology, and medicine get the big stuff wrong, you start from a place of skepticism. Ideally, we would look at the details in any given situation to make our final decisions on the credibility of experts because no two cases are alike. Unfortunately, we humans are not good at using facts and reason. We tend to use our biases and then rationalize them later.
So how do we know when to trust experts and when to be skeptical? Here are the red flags you should look for in order to know how much credibility to assign to the experts.
When the players have money on the line, the truth gets distorted. In climate science, money influences both sides of the debate. That’s a red flag.
Complexity with Assumptions
Whenever you see complexity, that is a red flag. Complexity is often used to deceive. And complexity invites human error. When you see complex models that claim to predict the future, stay skeptical, especially when humans are making assumptions that influence the results.
The exceptions are planetary predictions and other straightforward physics. We can predict the future location of planets without any human assumptions. That is just math and physics. But in the fields of finance and climate science, to name just two, humans are influencing the models with assumptions. That is always a red flag. I am aware of no complex prediction model populated with human assumption-tweaking that is credible, in any field. Is climate science the first exception? Maybe. But it would be unusual in my experience.
The Important Fact Left Out
When people have the facts on their side, they are quick to point it out. When a key fact is glaringly omitted, that’s a red flag.
In the world of climate science, most of you would not know the answer to this key question: Are the temperature measurements peer reviewed?
You probably assumed the temperature measurements are peer reviewed. Maybe some, or most, are. All I know for sure is that climate scientist Michael Mann says his temperature data is proprietary. He refused to release it to a Canadian court for that reason. is that a common situation, that data measurements are “secret.” I don’t know. Neither do you. That’s a red flag. It is conspicuous that you and I don’t know the answer to that basic question. Because if the raw temperature data is not peer reviewed, is it really science?
To be perfectly clear here, I don’t know the state of peer review for temperature measurements. But it is such a key question it raises a red flag as to why scientists aren’t making sure we know the raw data is clean and widely reviewed.
Conflation of Credibility
Whenever you see someone conflate a credible thing (such as the peer review system in science) with a less-credible thing (long term prediction models), that’s a red flag. If you question the accuracy of climate models, someone will mention the gold standard of peer review, even though that doesn’t address climate models that involve human assumptions. Conflation of credibility is a red flag.
My view on climate science is that different elements have different levels of earned credibility. Like this:
Basic Science: The chemistry and physics of climate change seem solid. When you add CO2 to an environment, expect some extra heat, all other things being equal.
Temperature Measurements: The temperature measurements used by climate scientists might be solid. But the way science has so far communicated this topic does not inspire confidence. I think you have to put a lower credibility on the temperature measurements than on the basic science, simply because of the way the topic is presented to the public. If the measurements are credible, why not tell us all about the peer review process that has validated them? And why would Michael Mann even have “proprietary” data? Isn’t everyone looking at the same stuff?
Climate Models: As soon as you hear that someone has a complicated prediction model, that’s red flag. If you hear that the model involves human assumptions and “tweaking,” that’s a double red flag. If you hear there are dozens of different models, that’s a triple red flag. If you hear that the models that don’t conform to the pack are discarded, and you don’t know why, that is a quadruple red flag. And if you see people conflating climate projections with economic models to put some credibility on the latter, you have a quintuple red flag situation.
To be fair, none of the so-called flags I mentioned means the models are wrong. But they do mean you can’t put the same credibility on them as you would the basic science.
Have you noticed that I seem to be the only person talking about economic models when it comes to climate change? That’s because there is a tendency to assume the economic decision is so obvious no study is needed.
That’s the sort of thinking that no economist would find credible. Moreover, economists don’t believe anyone can forecast the future with long term economic models. Science might tell us we have a big problem, but economists have to tell us when to start addressing it and how hard. That part is missing.
I have seen some economic guesses of how much damage would be caused by climate change. But I have not seen one that considered opportunity cost, or the benefit of waiting for better technology. No economist would respect a prediction that ignored those two enormous variables. And those variables are deeply unpredictable by their nature.
The One Sided Argument
When I see climate scientists in the media, they are never accompanied by skeptical scientists who can check their statements in real time. Likewise, articles by and about skeptics are usually presented without simultaneous debunking by the experts on the other side. Those are red flags. Any presentation of one side without the simultaneous fact-checking by the other is useless and almost certainly designed for persuasion, not truth. The problem here is that both sides of the climate debate are 100% persuasive when viewed without the other in attendance. If you think your side is the smart side, check out the other side. They look just as smart, at least to non-scientists such as me.
I’ll summarize by reminding readers that I am not a scientist and I don’t have the tools to evaluate the credibility of climate scientists. If you think you do have that ability as a non-scientist, my guess is that you are younger than me or you have less experience of the type I described above.
When I present this sort of framing to climate change believers, they generally retreat to Pascal’s Wager, which says in this case that we should treat any risk of catastrophe as if it is likely, so we aggressively address the risk and eliminate it. That makes sense in a world where resources are not constrained. But our world is the opposite. Everything we do is at the expense of something else we wanted to do. And I am aware of no economic model that considers the opportunity cost of spending a trillion dollars for perhaps a half-degree temperature improvement.
Climate change isn’t our only mortal threat. We have pandemics, terrorism, nuclear war, the singularity, asteroids, and probably a dozen more threats I don’t even know. If we could eliminate all of those threats and have money left over, I say let’s do it. But if resources are limited (and they are), I need a strong argument to put a trillion dollars into any one of the risks.
My new book, Win Bigly, is available for pre-order. It’s about persuasion in a world where facts don’t matter to our decisions. (Even when they should.)